Dynamic Prediction Method for Valuable Spare Parts Demand in Weaponry Equipment Based on Data Perception

Abstract

Missile is an important weapon system of the army. The spare parts of missile equipment are significant effect on military operations. In order to improve the mission completion rate of missile equipment in wartime, thispaper introduces data sensing method to forecast the demand of valuablespare parts of missile equipment dynamically. Firstly, the information related to valuable spare parts of missile equipment was obtained by data sensing, and the sample size was determined by Bernoulli uniform sampling probability. Secondly, according to the data quality of multisource and multi-modal, the data requirement for dynamic demand prediction of valuable spare parts of missile equipment was obtained. Finally, according to the characteristics of the spare parts, the life of the spare parts was predicted, realizing the dynamic prediction of the demand for valuable spare parts of missile equipment. The results show that the demand of valuable spare parts of missile equipment can be predicted dynamically by using this method, the accuracy is higher than 95%, and the real-time performance is more excellent.